Robust Early Pregnancy Prediction of Later Preeclampsia Using Metabolomic Biomarkers.
AuthorsKenny, Louise C
Broadhurst, David I
North, Robyn A
Cooper, Garth J S
Kell, Douglas B
Baker, Philip N
AffiliationAnu Research Centre, Department of Obstetrics and Gynaecology, University College Cork, Cork University Maternity Hospital, Cork, Ireland; School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester, United Kingdom; Division of Reproduction and Endocrinology, St Thomas Hospital, King's College London, London, United Kingdom; Department of Obstetrics and Gynaecology, Faculty of Medicine and Health Sciences, and School of Biological Sciences, University of Auckland, Auckland, New Zealand; Research Centre for Reproductive Health, Robinson Institute, School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, Australia; Department of Obstetrics and Gynecology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
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CitationRobust Early Pregnancy Prediction of Later Preeclampsia Using Metabolomic Biomarkers. 2010:notHypertension
AbstractPreeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15±1 weeks' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15±1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.
CollectionsJournal articles & published research
- First-trimester prediction of preeclampsia using metabolomic biomarkers: a discovery phase study.
- Authors: Odibo AO, Goetzinger KR, Odibo L, Cahill AG, Macones GA, Nelson DM, Dietzen DJ
- Issue date: 2011 Oct
- Early pregnancy prediction of preeclampsia in nulliparous women, combining clinical risk and biomarkers: the Screening for Pregnancy Endpoints (SCOPE) international cohort study.
- Authors: Kenny LC, Black MA, Poston L, Taylor R, Myers JE, Baker PN, McCowan LM, Simpson NA, Dekker GA, Roberts CT, Rodems K, Noland B, Raymundo M, Walker JJ, North RA
- Issue date: 2014 Sep
- Metabolic profiling uncovers a phenotypic signature of small for gestational age in early pregnancy.
- Authors: Horgan RP, Broadhurst DI, Walsh SK, Dunn WB, Brown M, Roberts CT, North RA, McCowan LM, Kell DB, Baker PN, Kenny LC
- Issue date: 2011 Aug 5
- Integrated proteomics pipeline yields novel biomarkers for predicting preeclampsia.
- Authors: Myers JE, Tuytten R, Thomas G, Laroy W, Kas K, Vanpoucke G, Roberts CT, Kenny LC, Simpson NA, Baker PN, North RA
- Issue date: 2013 Jun
- Validation of metabolomic models for prediction of early-onset preeclampsia.
- Authors: Bahado-Singh RO, Syngelaki A, Akolekar R, Mandal R, Bjondahl TC, Han B, Dong E, Bauer S, Alpay-Savasan Z, Graham S, Turkoglu O, Wishart DS, Nicolaides KH
- Issue date: 2015 Oct